• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.85-90
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• 2016

In this paper, the biometric data is transmitted in real time from the IoT environment is runoff, forgery, alteration, prevention of the factors that can be generated from a denial-of-service in advance, and the security strategy for the biometric data to protect the biometric data secure from security threats offer. The convenience of living in our surroundings to life with the development of ubiquitous computing and smart devices are available in real-time. And is also increasing interest in the IOT. IOT environment is giving the convenience of life. However, security threats to privacy also are exposed for 24 hours. This paper examines the security threats to biological data to be transmitted in real time from IOT environment. The technology for such security requirements and security technology according to the analysis of the threat. And with respect to the biometric data transmitted in real time on the IoT environment proposes a security strategy to ensure the stability against security threats and described with respect to its efficiency.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.196-204
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• 2024

The security of data and information using encryption algorithms is becoming increasingly important in today's world of digital data transmission over unsecured wired and wireless communication channels. Hybrid encryption techniques combine both symmetric and asymmetric encryption methods and provide more security than public or private key encryption models. Currently, there are many techniques on the market that use a combination of cryptographic algorithms and claim to provide higher data security. Many hybrid algorithms have failed to satisfy customers in securing data and cannot prevent all types of security threats. To improve the security of digital data, it is essential to develop novel and resilient security systems as it is inevitable in the digital era. The proposed hybrid algorithm is a combination of the well-known RSA algorithm and a simple symmetric key (SSK) algorithm. The aim of this study is to develop a better encryption method using RSA and a newly proposed symmetric SSK algorithm. We believe that the proposed hybrid cryptographic algorithm provides more security and privacy.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.6
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• pp.1225-1241
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• 2014

Recently, Financial companies implement DLP(Data Leaks Prevention) security products and enforce internal controls to prevent customer information leaks. Accidental data leaks in financial business increase more and more because internal controls are insufficient. Security officials and IT operation staffs struggle to plan countermeasures to respond to all kinds of accidental data leaks. It is difficult to prevent data leaks and to control information flow in business without research applications that handle business and privacy information. Therefore this paper describes business and privacy information flow on applications and how to plan and deploy security container based OS-level and Hypervisor virtualization technology to enforce internal controls for applications. After building security container, it was verified to implement internal controls and to prevent customer information leaks. With security policies additional security functions was implemented in security container and With recycling security container costs and time of response to security vulnerabilities was reduced.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.1
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• pp.157-167
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• 2020

The big data and artificial intelligence technology, which has provided the foundation for the recent 4th industrial revolution, has become a major driving force in business innovation across industries. In the field of information security, we are trying to develop and improve an intelligent security system by applying these techniques to large-scale log data, which has been difficult to find effective utilization methods before. The quality of security log big data, which is the basis of information security AI learning, is an important input factor that determines the performance of intelligent security system. However, the difference and complexity of log data by various product has a problem that requires excessive time and effort in preprocessing big data with poor data quality. In this study, we research and analyze the cases related to log data collection of various firewall. By proposing firewall log data collection format standard, we hope to contribute to the development of intelligent security systems based on security log big data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.15-23
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• 2015

This thesis proposes how data security has changed since the emergence of 'Big Data' in 2012 and the type of Integrated Security Management System that needs to be built against security threats, based on an analysis of Big Data. Much research has been conducted in Big Data. I need to think about what an Integrated Security Management System requires in order to safeguard against security threats such as APT. I would like to draw a comparison between the current Integrated Security Management System and one that is based on Big Data, including its limitations and improvements, so that I can suggest a much improved version of Integrated Security Management System.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.299-307
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• 2014

N-Data Center which provide of cloud computing service for the Government departments, will be prepared transforming to cloud data center and transformed into an 'IT service' provided as a service to the information resources required by each department. N-Data center already provide a cloud service to the departments as maintains a high level of security, and plan to connecting with the private sector as a precondition of security. Therefore, in order to promote them effectively, it is necessary to determine the level of security in the cloud data center, and we have proposed appropriate measures. In this paper, we analyze security requirements of cloud data centers in developed countries and identify the leading private cloud data center security. In addition, we identify the N-data center security level, and analyzes the data center and private cloud gap and provide a transition strategy in terms of security finally.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.2
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• pp.439-449
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• 2019

The development of information technology represented by ICBMA (IoT, Cloud, Big Data, Mobile, AI), is leading to a surge in data and a numerical and quantitative increase in data centers to accommodate it. As the data center is recognized as a social infrastructure, It is very important to identify physical security threats in advance in order to secure safety, such as responding to a terrorist attack. In this paper, we develop physical security threat breakdown structure (PS-TBS) for easy identification and classification of threats, and verify the feasibility and effectiveness of the PS-TBS through expert questionnaires. In addition, we intend to contribute to the improvement of physical security level by practical use in detailed definition on items of PS-TBS.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.67-76
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• 2024

The Internet of Things (IoT) has revolutionized communication and device operation, but it has also brought significant security challenges. IoT networks are structured into four levels: devices, networks, applications, and services, each with specific security considerations. Personal Area Networks (PANs), Local Area Networks (LANs), and Wide Area Networks (WANs) are the three types of IoT networks, each with unique security requirements. Communication protocols such as Wi-Fi and Bluetooth, commonly used in IoT networks, are susceptible to vulnerabilities and require additional security measures. Apart from physical security, authentication, encryption, software vulnerabilities, DoS attacks, data privacy, and supply chain security pose significant challenges. Ensuring the security of IoT devices and the data they exchange is crucial. This paper utilizes the Random Forest Algorithm from machine learning to detect anomalous data in IoT devices. The dataset consists of environmental data (temperature and humidity) collected from IoT sensors in Oman. The Random Forest Algorithm is implemented and trained using Python, and the accuracy and results of the model are discussed, demonstrating the effectiveness of Random Forest for detecting IoT device data anomalies.

• Informatization Policy
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• v.23 no.1
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• pp.3-19
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• 2016

The purpose of the study is to analyze the existing literature and to suggest future research directions in the big data security area. This study identifies 62 research articles and analyses their publication year, publication media, general research approach, specific research method, and research topic. According to the results of the analyses, big data security research is at its intial stage in which non-empirical studies and research dealing with technical issues are dominant. From the research topic perspective, the area demonstrates the signs of initial research stage in which proportion of the macro studies dealing with overall issues is far higher than the micro ones covering specific implementation methods and sectoral issues. A few promising topics for future research include overarching framework on big data security, big data security methods for different industries, and government policies on big data security. Currently, the big data security area does not have sufficient research results. In the future, studies covering various topics in big data security from multiple perspectives are anticipated.

• Convergence Security Journal
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• v.23 no.1
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• pp.109-115
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• 2023

The future outlook for defense faces various and challenging environments such as the acceleration of uncertainty in the global security landscape and limitations in domestic social and economic conditions. In response, the Ministry of National Defense seeks to address the problems and threats through defense innovation based on scientific and technological advancements such as artificial intelligence, drones, and robots. To introduce advanced AI-based technology, it is essential to integrate and utilize data on IT environments such as cloud and 5G. However, existing traditional security policies face difficulties in data sharing and utilization due to mainly system-oriented security policies and uniform security measures. This study proposes a paradigm shift to a data value-based security policy based on theoretical background on data valuation and life-cycle management. Through this, it is expected to facilitate the implementation of scientific and technological innovations for national defense based on data-based task activation and new technology introduction.